197 citations · 292 across the 54 of their papers we have counts for
14 papers · 1 filter
Conditional Variational Autoencoders for Probabilistic Pose Regression
Fereidoon Zangeneh, Leonard Bruns, Amit Dekel +2
Robots rely on visual relocalization to estimate their pose from camera images when they lose track. One of the challenges in visual relocalization is repetitive structures in the…
Fusion in Context: A Multimodal Approach to Affective State Recognition
Youssef Mohamed, Severin Lemaignan, Arzu Guneysu +2
Accurate recognition of human emotions is a crucial challenge in affective computing and human-robot interaction (HRI). Emotional states play a vital role in shaping behaviors, dec…
ExelMap: Explainable Element-based HD-Map Change Detection and Update
Lena Wild, Ludvig Ericson, Rafael Valencia +1
Acquisition and maintenance are central problems in deploying high-definition (HD) maps for autonomous driving, with two lines of research prevalent in current literature: Online H…
HD-maps as Prior Information for Globally Consistent Mapping in GPS-denied Environments
Waqas Ali, Patric Jensfelt, Thien-Minh Nguyen
In recent years, prior maps have become a mainstream tool in autonomous navigation. However, commonly available prior maps are still tailored to control-and-decision tasks, and the…
SeFlow: A Self-Supervised Scene Flow Method in Autonomous Driving
Qingwen Zhang, Yi Yang, Peizheng Li +2
Scene flow estimation predicts the 3D motion at each point in successive LiDAR scans. This detailed, point-level, information can help autonomous vehicles to accurately predict and…
Beyond the Frontier: Predicting Unseen Walls from Occupancy Grids by Learning from Floor Plans
Ludvig Ericson, Patric Jensfelt
In this paper, we tackle the challenge of predicting the unseen walls of a partially observed environment as a set of 2D line segments, conditioned on occupancy grids integrated al…
BeautyMap: Binary-Encoded Adaptable Ground Matrix for Dynamic Points Removal in Global Maps
Mingkai Jia, Qingwen Zhang, Bowen Yang +3
Global point clouds that correctly represent the static environment features can facilitate accurate localization and robust path planning. However, dynamic objects introduce undes…
Neural Graph Map: Dense Mapping with Efficient Loop Closure Integration
Leonard Bruns, Jun Zhang, Patric Jensfelt
Neural field-based SLAM methods typically employ a single, monolithic field as their scene representation. This prevents efficient incorporation of loop closure constraints and lim…
DUFOMap: Efficient Dynamic Awareness Mapping
Daniel Duberg, Qingwen Zhang, MingKai Jia +1
The dynamic nature of the real world is one of the main challenges in robotics. The first step in dealing with it is to detect which parts of the world are dynamic. A typical bench…
Addressing Data Annotation Challenges in Multiple Sensors: A Solution for Scania Collected Datasets
Ajinkya Khoche, Aron Asefaw, Alejandro Gonzalez +3
Data annotation in autonomous vehicles is a critical step in the development of Deep Neural Network (DNN) based models or the performance evaluation of the perception system. This…
MCD: Diverse Large-Scale Multi-Campus Dataset for Robot Perception
Thien-Minh Nguyen, Shenghai Yuan, Thien Hoang Nguyen +8
Perception plays a crucial role in various robot applications. However, existing well-annotated datasets are biased towards autonomous driving scenarios, while unlabelled SLAM data…
UADA3D: Unsupervised Adversarial Domain Adaptation for 3D Object Detection with Sparse LiDAR and Large Domain Gaps
Maciej K Wozniak, Mattias Hansson, Marko Thiel +1
In this study, we address a gap in existing unsupervised domain adaptation approaches on LiDAR-based 3D object detection, which have predominantly concentrated on adapting between…
DeFlow: Decoder of Scene Flow Network in Autonomous Driving
Qingwen Zhang, Yi Yang, Heng Fang +2
Scene flow estimation determines a scene's 3D motion field, by predicting the motion of points in the scene, especially for aiding tasks in autonomous driving. Many networks with l…
Transitional Grid Maps: Joint Modeling of Static and Dynamic Occupancy
José Manuel Gaspar Sánchez, Leonard Bruns, Jana Tumova +2
Autonomous agents rely on sensor data to construct representations of their environments, essential for predicting future events and planning their actions. However, sensor measure…